Longitudinal changes of structural and functional connectivity in multiple sclerosis in a natural history cohort and during an exercise trial

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Multiple Sclerosis (MS) is the most common autoimmune disease of the central nervous system (CNS). It affects mainly young adults and leads to an accumulation of disability by inflammation as well as by progressive neurodegeneration. Exercises are currently the best neuroprotective treatment as approved drugs reduce inflammation only. Magnetic resonance tomography (MRI) monitors inflammation but quantifying neurodegeneration is restricted and weakly associated with cognition, mobility or vision.From a neuroscientific perspective, the brain can be considered a densely connected network and MS affects the networks architecture and function. MRI allows investigating functional connectivity by resting state functional MRI (fMRI) as well as structural connectivity. Graph theoretic measures are mathematical models to analyse such networks. This approach has only been applied in one longitudinal study with MS patients. A compensatory increase in functional connectivity in the early phase of the diseases seems preceding a long-term decrease associated with disability accumulation. Natural history data and exercise trials are providing the best scientific framework to further develop MRI-based connectivity analysis for proving as a highly specific biomarker linked to disability. The overarching aim of this project is to provide a comprehensive profile of structural and functional CNS network disturbance and reorganisation in relapsing-remitting MS patients and their clinical correlates. The analysis follows a fMRI study from the hosting institution in Marseille combined with structural network analyses, which I have established already. The proposal includes two datasets based on the same MRI protocol and extensive neuropsychological profile at each time-point: A natural history cohort (n = 38 and matched healthy controls, annual follow-up of two years, completed in February 2017) and a randomised waiting-group controlled exercise trial (n = 60, follow-up after three and six months, completed in July 2016). I will reconstruct structural and functional networks and investigate if structural changes (e.g. loss of connections) lead to functional reorganisation over two years in the natural history cohort. Cognition will serve as the main clinical outcome and changes of global graph metrics and network architecture are compared to healthy controls. Next, I aim to compare standard resting state MRI analysis with so called functional connectivity dynamics, which have not been applied to MS. This approach takes into account that activation of networks varies during the recording period. For the exercise trial, I will compare graph metrics and network architecture pre-post exercise as well as between waiting and intervention group. My findings will elucidate the impact of exercises on functional and structural brain networks. I will further develop network connectivity as highly specific and clinically meaningful outcome measure of neurodegeneration in MS.